{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import joblib\n",
    "import warnings\n",
    "import collections\n",
    "from itertools import zip_longest\n",
    "\n",
    "# from sklearn.gaussian_process import GaussianProcessRegressor\n",
    "# from sklearn.gaussian_process.kernels import DotProduct, WhiteKernel, RBF, ConstantKernel\n",
    "\n",
    "# from sklearn.linear_model import LinearRegression\n",
    "\n",
    "from scipy.optimize import curve_fit\n",
    "import GPy\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_data(data_no=1): \n",
    "    data = joblib.load('./test_HA/test_HA_0%d.lz4'%data_no) \n",
    "    return data\n",
    "\n",
    "def cl_mean(mean_list, seg_cl, up_thred = 30, down_thred= 0, confidence=0.5):\n",
    "    mean_list_copy = mean_list.copy()\n",
    "     # 标记超出阈值的样本为-1\n",
    "    for i in range(len(mean_list)):\n",
    "        idx_mean = mean_list[i]\n",
    "        if (idx_mean>up_thred) or (idx_mean<down_thred):\n",
    "            mean_list[i] = -1\n",
    "    \n",
    "    # 拟合粗趋势\n",
    "    ser = pd.Series(mean_list)\n",
    "    ser.index = seg_cl #index\n",
    "    if sum(ser != -1)<=1:\n",
    "        print('超出阈值的样本数量过多！')\n",
    "    x_train = ser.index[ser != -1].values\n",
    "    y_train = ser[ser != -1].values\n",
    "    \n",
    "    f1 = np.polyfit(x_train, y_train, 2)\n",
    "    p1 = np.poly1d(f1)\n",
    "    tmp = p1(seg_cl)\n",
    "    mean_list = list(tmp)\n",
    "    \n",
    "    # 纠正\n",
    "    for i in range(len(mean_list)):\n",
    "        idx_mean = mean_list_copy[i]\n",
    "        cmp_mean = mean_list[i]\n",
    "        if np.abs(idx_mean - cmp_mean) >= confidence:\n",
    "            pass\n",
    "        else:\n",
    "            mean_list[i] = idx_mean \n",
    "            \n",
    "    return seg_cl, mean_list, p1\n",
    "\n",
    "def CL_mean_auto(df, apply_col, seg_col, up_thred = 30, down_thred= 0, use_predict=True):\n",
    "    '''\n",
    "    描述：\n",
    "        统计每一段时间的某一列均值，并拟合曲线\n",
    "    '''\n",
    "    data = df[apply_col]\n",
    "    seg_cl = df[seg_col].unique()\n",
    "    seg_cl.sort()\n",
    "    \n",
    "    \n",
    "    # 初始化delta_list\n",
    "    mean_list = []\n",
    "    for cl in seg_cl:\n",
    "        seg_mean = data[df[seg_col] == cl].mean()\n",
    "        mean_list.append(seg_mean)\n",
    "    if not use_predict:\n",
    "        return mean_list\n",
    "    \n",
    "    seg_cl, mean_list, _ = cl_mean(mean_list, seg_cl, up_thred, down_thred= 0, confidence=1.5)   \n",
    "    return seg_cl, mean_list\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cl_percent_delta(delta_list, seg_cl, up_thred=30, down_thred=0, confidence=0.5):\n",
    "    delta_list_copy = delta_list.copy()\n",
    "    \n",
    "    # 标记超出阈值的样本为-1\n",
    "    for i in range(len(delta_list)):\n",
    "        idx_delta = delta_list[i]\n",
    "        if (idx_delta>up_thred) or (idx_delta<down_thred):\n",
    "            delta_list[i] = -1\n",
    "    \n",
    "    # 拟合粗趋势\n",
    "    ser = pd.Series(delta_list)\n",
    "    ser.index = seg_cl #index\n",
    "    if sum(ser != -1)<=1:\n",
    "        print('超出阈值的样本数量过多！')\n",
    "    x_train = ser.index[ser != -1].values\n",
    "    y_train = ser[ser != -1].values\n",
    "    \n",
    "    f1 = np.polyfit(x_train, y_train, 2)\n",
    "    p1 = np.poly1d(f1)\n",
    "    tmp = p1(seg_cl)\n",
    "    delta_list = list(tmp)\n",
    "    print(delta_list)\n",
    "     # 纠正\n",
    "    for i in range(len(delta_list)):\n",
    "        idx_delta = delta_list_copy[i]\n",
    "        cmp_delta = delta_list[i]\n",
    "        if np.abs(idx_delta - cmp_delta) >= confidence:\n",
    "            pass\n",
    "        else:\n",
    "            delta_list[i] = idx_delta \n",
    "    return seg_cl, delta_list\n",
    "\n",
    "def CL_percent_delta_auto(df, apply_col, seg_col, up_box=90, down_box=10, up_thred=10, down_thred=0, use_predict = True):\n",
    "    '''\n",
    "    描述：\n",
    "        统计每一段时间的某一列变化范围，并拟合曲线， 不需给出correct_idx\n",
    "    '''\n",
    "    data = df[apply_col]\n",
    "    seg_cl = df[seg_col].unique()\n",
    "    seg_cl.sort()\n",
    "    \n",
    "    # 初始化delta_list\n",
    "    delta_list = []\n",
    "    for cl in seg_cl:\n",
    "        tmp = data[df[seg_col] == cl]\n",
    "        up_bound = np.percentile(tmp, up_box)\n",
    "        down_bound = np.percentile(tmp, down_box)\n",
    "        cl_delta = up_bound - down_bound\n",
    "        delta_list.append(cl_delta)\n",
    "    if not use_predict:\n",
    "        return seg_cl, delta_list\n",
    "    cl, delta_list = cl_percent_delta(delta_list, seg_cl, up_thred, down_thred, confidence=2.5) \n",
    "    return seg_cl, delta_list\n",
    "            \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'test_01' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-4-a45d77128edd>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m16\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mcl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdelta_list\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCL_percent_delta_auto\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest_01\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'PCA_T2'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'CLI'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mup_box\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m95\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdown_box\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mup_thred\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdown_thred\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0muse_predict\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0;31m# cl, delta_list = cl_percent_delta(delta_list, cl, up_thred=30, down_thred=0, confidence=0.1)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m11\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdelta_list\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'train_01'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'test_01' is not defined"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1152x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,8))\n",
    "cl, delta_list = CL_percent_delta_auto(test_01, 'PCA_T2', 'CLI', up_box=95, down_box=5, up_thred=10, down_thred=0, use_predict=True)\n",
    "# cl, delta_list = cl_percent_delta(delta_list, cl, up_thred=30, down_thred=0, confidence=0.1)\n",
    "plt.plot(range(1,11), delta_list, label='train_01')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_01 = joblib.load('./test_HA/test_HA_01.lz4')\n",
    "test_02 = joblib.load('./test_HA/test_HA_02.lz4')\n",
    "test_03 = joblib.load('./test_HA/test_HA_03.lz4')\n",
    "test_04 = joblib.load('./test_HA/test_HA_04.lz4')\n",
    "test_05 = joblib.load('./test_HA/test_HA_05.lz4')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_01 = joblib.load('./train_HA/train_HA_01.lz4')\n",
    "train_02 = joblib.load('./train_HA/train_HA_02.lz4')\n",
    "train_03 = joblib.load('./train_HA/train_HA_03.lz4')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算均值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f9f1ec51518>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cl, mean_list = CL_mean_auto(test_01, 'PCA_T2', 'CLI', 30, 0, use_predict=True)\n",
    "cl, mean_list, _ = cl_mean(mean_list, cl, confidence=0.3)\n",
    "plt.plot( mean_list, label='test_01')\n",
    "\n",
    "cl, mean_list = CL_mean_auto(test_02, 'PCA_T2', 'CLI', 30, 0, use_predict=True)\n",
    "cl, mean_list, _ = cl_mean(mean_list, cl, confidence=0.3)\n",
    "plt.plot( mean_list, label='test_02')\n",
    "\n",
    "cl, mean_list = CL_mean_auto(test_03, 'PCA_T2', 'CLI', 30, 0, use_predict=True)\n",
    "cl, mean_list, _ = cl_mean(mean_list, cl, confidence=0.3)\n",
    "plt.plot( mean_list, label='test_03')\n",
    "\n",
    "cl, mean_list = CL_mean_auto(test_04, 'PCA_T2', 'CLI', 30, 0, use_predict=True)\n",
    "cl, mean_list, _ = cl_mean(mean_list, cl, confidence=0.3)\n",
    "plt.plot( mean_list, label='test_04')\n",
    "\n",
    "cl, mean_list = CL_mean_auto(test_05, 'PCA_T2', 'CLI', 30, 0, use_predict=True)\n",
    "cl, mean_list, _ = cl_mean(mean_list, cl, confidence=0.3)\n",
    "plt.plot( mean_list, label='test_05')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f9f1eae9748>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,8))\n",
    "cl, mean_list = CL_mean_auto(train_01, 'PCA_T2', 'CLI', 30, 0, use_predict=True)\n",
    "cl, mean_list, p = cl_mean(mean_list, cl, confidence=0.3)\n",
    "mean_list[0] = 0\n",
    "plt.plot(range(1,49), mean_list, label='train_01')\n",
    "\n",
    "cl, mean_list = CL_mean_auto(train_02,  'PCA_T2', 'CLI', 30, 0, use_predict=True)\n",
    "cl, mean_list, p = cl_mean(mean_list, cl, confidence=0.3)\n",
    "mean_list[0] = 0\n",
    "plt.plot(range(1,49), mean_list, label='train_02')\n",
    "\n",
    "cl, mean_list = CL_mean_auto(train_03, 'PCA_T2', 'CLI', 30, 0, use_predict=True)\n",
    "cl, mean_list, p = cl_mean(mean_list, cl, confidence=0.3)\n",
    "mean_list[0] = 0\n",
    "plt.plot(range(1,38), mean_list, label='train_03')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 变化幅度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.27584666010831194, 0.278595605309329, 0.2813643966292841, 0.2841530340681772, 0.28696151762600836, 0.28978984730277757, 0.29263802309848475, 0.29550604501313, 0.2983939130467132, 0.3013016271992345, 0.3042291874706938, 0.3071765938610911, 0.31014384637042647, 0.3131309449986998, 0.3161378897459112, 0.31916468061206066, 0.3222113175971481, 0.32527780070117357, 0.32836412992413705, 0.3314703052660386, 0.3345963267268781, 0.3377421943066557, 0.3409079080053713, 0.3440934678230249, 0.34729887375961654, 0.35052412581514625, 0.3537692239896139, 0.3570341682830196, 0.36031895869536334, 0.3636235952266451, 0.3669480778768649, 0.37029240664602275, 0.37365658153411857, 0.37704060254115246, 0.3804444696671243, 0.38386818291203423, 0.38731174227588216, 0.3907751477586682, 0.39425839936039214, 0.3977614970810541, 0.4012844409206542, 0.40482723087919226, 0.40838986695666835, 0.41197234915308245, 0.4155746774684346, 0.4191968519027247, 0.4228388724559529, 0.42650073912811914]\n",
      "[1.0586037911738826, 1.0547067894861684, 1.0512881241599776, 1.0483477951953102, 1.0458858025921662, 1.0439021463505458, 1.0423968264704486, 1.041369842951875, 1.0408211957948246, 1.0407508849992977, 1.0411589105652943, 1.0420452724928144, 1.0434099707818578, 1.0452530054324245, 1.0475743764445147, 1.0503740838181284, 1.0536521275532655, 1.057408507649926, 1.06164322410811, 1.0663562769278172, 1.0715476661090482, 1.0772173916518022, 1.08336545355608, 1.089991851821881, 1.0970965864492053, 1.1046796574380533, 1.1127410647884246, 1.1212808085003192, 1.1302988885737373, 1.1397953050086789, 1.149770057805144, 1.1602231469631323, 1.1711545724826442, 1.1825643343636794, 1.194452432606238, 1.2068188672103202, 1.2196636381759256, 1.2329867455030545, 1.246788189191707, 1.2610679692418827, 1.275826085653582, 1.2910625384268044, 1.3067773275615506, 1.32297045305782, 1.339641914915613, 1.3567917131349292, 1.3744198477157687, 1.392526318658132]\n",
      "[0.5990483404602308, 0.4849836620781042, 0.38163581250890677, 0.28900479175263843, 0.20709059980929923, 0.13589323667888908, 0.07541270236140829, 0.02564899685685651, -0.013397879834766147, -0.04172792771345957, -0.059341146779223974, -0.06623753703205915, -0.06241709847196519, -0.04787983109894223, -0.022625734912990025, 0.013345190085891412, 0.060032943897701974, 0.11743752652244166, 0.18555893796011047, 0.2643971782107084, 0.3539522472742352, 0.4542241451506914, 0.5652128718400768, 0.6869184273423914, 0.8193408116576351, 0.9624800247858079, 1.1163360667269098, 1.2809089374809406, 1.4561986370479008, 1.6422051654277903, 1.8389285226206091, 2.0463687086263564, 2.2645257234450327, 2.493399567076639, 2.7329902395211736, 2.9832977407786387, 3.2443220708490315]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f9f254e6f98>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,8))\n",
    "cl, delta_list = CL_percent_delta_auto(train_01, 'PCA_T2', 'CLI', up_box=95, down_box=5, up_thred=10, down_thred=0, use_predict=True)\n",
    "# cl, delta_list = cl_percent_delta(delta_list, cl, up_thred=30, down_thred=0, confidence=0.1)\n",
    "plt.plot(range(1,49), delta_list, label='train_01')\n",
    "\n",
    "cl, delta_list = CL_percent_delta_auto(train_02, 'PCA_T2', 'CLI', up_box=95, down_box=5, up_thred=10, down_thred=0, use_predict=True)\n",
    "# cl, delta_list = cl_percent_delta(delta_list, cl, up_thred=30, down_thred=0,  confidence=0.1)\n",
    "plt.plot(range(1,49), delta_list, label='train_02')\n",
    "\n",
    "cl, delta_list = CL_percent_delta_auto(train_03, 'PCA_T2', 'CLI', up_box=95, down_box=5, up_thred=10, down_thred=0, use_predict=True)\n",
    "# cl, delta_list = cl_percent_delta(delta_list, cl, up_thred=30, down_thred=0,  confidence=0.1)\n",
    "plt.plot(range(1,38), delta_list, label='train_03')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.5463521156319032, 0.5711657056153707, 0.5944911682331712, 0.6163285034853043, 0.6366777113717704, 0.6555387918925693, 0.672911745047701, 0.6887965708371655, 0.703193269260963, 0.7161018403190932, 0.7275222840115563, 0.7374546003383522, 0.7458987892994808, 0.7528548508949424, 0.7583227851247368, 0.7623025919888641, 0.7647942714873242, 0.7657978236201171, 0.7653132483872428, 0.7633405457887013, 0.7598797158244927, 0.754930758494617, 0.7484936737990739, 0.7405684617378638, 0.7311551223109867, 0.7202536555184422, 0.7078640613602305, 0.6939863398363518, 0.6786204909468058, 0.6617665146915928, 0.6434244110707125, 0.6235941800841651, 0.6022758217319504, 0.5794693360140687, 0.5551747229305197, 0.5293919824813036, 0.5021211146664204, 0.47336211948587, 0.44311499693965223, 0.41137974702776753, 0.37815636975021566, 0.34344486510699646, 0.30724523309811025, 0.2695574737235568, 0.2303815869833361, 0.1897175728774484, 0.1475654314058935, 0.10392516256867129]\n",
      "[0.5281783122730251, 0.750285859714891, 0.9629667223583122, 1.1662209002032886, 1.3600483932498204, 1.5444492014979074, 1.71942332494755, 1.8849707635987476, 2.0410915174515, 2.187785586505809, 2.3250529707616723, 2.4528936702190913, 2.5713076848780654, 2.6802950147385953, 2.7798556598006794, 2.8699896200643193, 2.950696895529515, 3.021977486196266, 3.083831392064572, 3.1362586131344337, 3.1792591494058495, 3.2128330008788213, 3.236980167553349, 3.2517006494294316, 3.2569944465070693, 3.252861558786262, 3.2393019862670105, 3.216315728949314, 3.1839027868331735, 3.142063159918588, 3.0907968482055574, 3.030103851694082, 2.9599841703841623, 2.8804378042757977, 2.791464753368988, 2.6930650176637343, 2.5852385971600356, 2.4679854918578936, 2.341305701757305, 2.2051992268582725, 2.059666067160795, 1.9047062226648728, 1.740319693370506, 1.5665064792776944, 1.3832665803864381, 1.190599996696737, 0.9885067282085914, 0.776986774922001]\n",
      "[3.3595879898210836, 3.0150516117278476, 2.697180139598449, 2.405973573432888, 2.141431913231165, 1.9035551589932798, 1.6923433107192318, 1.5077963684090214, 1.3499143320626494, 1.218697201680114, 1.1141449772614171, 1.0362576588065573, 0.985035246315535, 0.960477739788351, 0.9625851392250042, 0.9913574446254954, 1.046794655989824, 1.1288967733179902, 1.237663796609994, 1.3730957258658352, 1.5351925610855148, 1.7239543022690316, 1.9393809494163858, 2.1814725025275776, 2.4502289616026083, 2.7456503266414742, 3.06773659764418, 3.416487774610723, 3.791903857541102, 4.193984846435321, 4.622730741293378, 5.078141542115269, 5.560217248901001, 6.068957861650571, 6.604363380363974, 7.166433805041219, 7.7551691356823]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f9f259b49e8>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,8))\n",
    "cl, delta_list = CL_percent_delta_auto(train_01, 'PCA_T2', 'CLI', up_box=95, down_box=5, up_thred=10, down_thred=0, use_predict=False)\n",
    "cl, delta_list = cl_percent_delta(delta_list, cl, up_thred=30, down_thred=0, confidence=0.1)\n",
    "plt.plot(range(1,49), delta_list, label='train_01')\n",
    "\n",
    "cl, delta_list = CL_percent_delta_auto(train_02, 'PCA_T2', 'CLI', up_box=95, down_box=5, up_thred=10, down_thred=0, use_predict=False)\n",
    "cl, delta_list = cl_percent_delta(delta_list, cl, up_thred=30, down_thred=0,  confidence=0.1)\n",
    "plt.plot(range(1,49), delta_list, label='train_02')\n",
    "\n",
    "cl, delta_list = CL_percent_delta_auto(train_03, 'PCA_T2', 'CLI', up_box=95, down_box=5, up_thred=10, down_thred=0, use_predict=False)\n",
    "cl, delta_list = cl_percent_delta(delta_list, cl, up_thred=30, down_thred=0,  confidence=0.1)\n",
    "plt.plot(range(1,38), delta_list, label='train_03')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-0.06930623245717449, 0.22551643054181358, 0.47394380298229155, 0.6759758848642603, 0.8316126761877172, 0.9408541769526657, 1.0037003871591033, 0.990206935896448]\n",
      "[2.7651627865562443, 2.7297732874387677, 2.4323729942397616, 2.1703622001582294, 1.419719317031113, 0.9310872279855298, -0.2727982450696942]\n",
      "[0.17899443008223603, 0.17464596719518485, 0.17066870440169737, 0.1670626417017736, 0.16382777909541357, 0.16096411658261728, 0.15847165416338466, 0.15635039183771576, 0.1546003296056106, 0.15322146746706916]\n",
      "[0.4482366668332415, 0.4316081480562243, 0.4113320673185365, 0.38740842462017805, 0.35983721996114904, 0.3286184533414495, 0.29375212476107937, 0.25523823422003855, 0.21307678171832728, 0.16726776725594544]\n",
      "[0.20508990661864424, 0.19454641641771686, 0.1860035987572748, 0.17946145363731802, 0.17491998105784656, 0.17237918101886052, 0.17183905352035977, 0.17329959856234434, 0.17676081614481443, 0.1822227062677696]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f9f25896f28>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,8))\n",
    "cl, delta_list = CL_percent_delta_auto(test_01, 'PCA_T2', 'CLI', up_box=95, down_box=5, up_thred=10, down_thred=0, use_predict=False)\n",
    "cl, delta_list = cl_percent_delta(delta_list, cl, up_thred=30, down_thred=0, confidence=0.1)\n",
    "plt.plot(delta_list, label='train_01')\n",
    "\n",
    "cl, delta_list = CL_percent_delta_auto(test_02, 'PCA_T2', 'CLI', up_box=95, down_box=5, up_thred=10, down_thred=0, use_predict=False)\n",
    "cl, delta_list = cl_percent_delta(delta_list, cl, up_thred=30, down_thred=0,  confidence=0.1)\n",
    "plt.plot(delta_list, label='train_02')\n",
    "\n",
    "cl, delta_list = CL_percent_delta_auto(test_03, 'PCA_T2', 'CLI', up_box=95, down_box=5, up_thred=10, down_thred=0, use_predict=False)\n",
    "cl, delta_list = cl_percent_delta(delta_list, cl, up_thred=30, down_thred=0,  confidence=0.1)\n",
    "plt.plot(delta_list, label='train_03')\n",
    "\n",
    "cl, delta_list = CL_percent_delta_auto(test_04, 'PCA_T2', 'CLI', up_box=95, down_box=5, up_thred=10, down_thred=0, use_predict=False)\n",
    "cl, delta_list = cl_percent_delta(delta_list, cl, up_thred=30, down_thred=0,  confidence=0.1)\n",
    "plt.plot(delta_list, label='train_04')\n",
    "\n",
    "cl, delta_list = CL_percent_delta_auto(test_05, 'PCA_T2', 'CLI', up_box=95, down_box=5, up_thred=10, down_thred=0, use_predict=False)\n",
    "cl, delta_list = cl_percent_delta(delta_list, cl, up_thred=30, down_thred=0,  confidence=0.1)\n",
    "plt.plot(delta_list, label='train_05')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
